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Table 1 Comparison of secondary structure prediction methods on the CB513 benchmark dataset

From: Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure

Method Q3(%) SOV(%) MCCH MCCE MCCL
SVMpsi 76.6 73.5 0.68 0.60 0.56
JNET 76.9 N/A N/A N/A N/A
YASSPP 77.8 75.1 0.58 0.64 0.71
DBNfinal 76.3 72.7 0.71 0.61 0.57
DBNpred 77.3 73.0 0.74 0.61 0.59
DBNN 78.1 74.0 0.74 0.64 0.60
PSIPRED 78.2 77.3 N/A N/A N/A
SVM_D3 78.4 N/A N/A N/A N/A
DESTRUCT 79.4 77.5 N/A N/A N/A
DISSPred 80.0 N/A 0.77 0.68 0.62
DSPRED 80.3 77.7 0.78 0.68 0.63